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57 results for “bilingualism”
Emergent Bilinguals: Child Language Proficiency and Language of Treatment
ClinicalTrials.gov study NCT06866223. IPD Sharing: YES. Countries: 1. Publications: 0.
The Relationship Between Child Language Proficiency and Language of Treatment on the Outcomes of Bilingual Children with Developmental Language Disorder
ClinicalTrials.gov study NCT06085300. IPD Sharing: YES. Countries: 1. Publications: 0.
BILINGUALISM AND BRAIN HEALTH: HOW LEARNING A NEW LANGUAGE STRENGTHENS COGNITIVE ABILITIES
Open the record for dataset details and reuse information.
Treatment Targets in Spanish and English Bilingual Speech Intervention
ClinicalTrials.gov study NCT06416306. IPD Sharing: NO. Countries: 1. Publications: 0.
Neural Correlates of Language Control in Bilinguals. Functional MRI and Stimulation Mapping Data in Awake Surgery.
ClinicalTrials.gov study NCT02391493. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Cooking for Your Health in Southern New Mexico: an 8-week, Bilingual (English and Spanish) Nutritional Intervention in Adults Living in Doña Ana and Otero Counties
ClinicalTrials.gov study NCT06609057. IPD Sharing: NO. Countries: 1. Publications: 0.
Bilingual Breast Cancer Educational Intervention for Hispanic Women With Stage I, Stage II, or Stage III Breast Cancer and Their Families or Caregivers
ClinicalTrials.gov study NCT01043003. IPD Sharing: Not stated. Countries: 1. Publications: 0.
A Bilingual Virtually-based Intervention (PEDALL) for the Prevention of Weight Gain in Childhood ALL Patients Considering Key Genetic and Sociodemographic Risk Factors
ClinicalTrials.gov study NCT05963971. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Bilingualism: Validation Of "Avicenne's Elal"
ClinicalTrials.gov study NCT01331057. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Bilingual Family Literacy Program Pilot
ClinicalTrials.gov study NCT04423133. IPD Sharing: NO. Countries: 1. Publications: 0.
Educational Support Group Program for Bilingual and Spanish-speaking Carepartners and People With Progressive Aphasia
ClinicalTrials.gov study NCT06511752. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Traceability Solutions for Supporting Intermingled-Bilingual Artifacts
<p>Bilingual software engineering dataset for issues and commits</p>
Remote Screening for Developmental Language Disorder in Bilingual Children: Preliminary Validation in Spanish–Italian Speaking Preschool Children
<p>The file contains the data collected from a sample of Spanish-Italian speaking preschool children who were tested with the MuLiMi platform for the validation of the tasks implemented there. The tests (language tasks) have the aim to allow identification of risk of Developmental Language Disorder in the bilingual population. The file is in Italian but English translation is provided for all variables. The bigram "sp" in the variable name indicates Spanish, "it" indicates Italian.</p>
Bilingual inscription Tomb FA-5, Mleiha, Sharjah
Bilingual South-Arabian / Aramaic funerary inscription discovered inside the burial chamber of tomb FA-5, Mleiha, Sharjah, UAE. (Overlaet 2018:14 Figure 9, Catalog No. 1). Central panel in south Arabian script, text along the rim in Aramaic. Text reads "Memorial and tomb of Amud son of Gurr son of Ali, inspector of the king of Oman, which built over him his son Amud son of Amud son if Gurr, inspector of the king of Oman." Dated to either 222/221 or 215/214 BCE. First record evidence of an Oman Kingdom (Overlaet 2018:13). Model of the cast of the original before restoration. 358 photos. Completely processed (aligned, scaled, modeled, cleaned, simplified, unwrapped, textured, meshed) in Reality Capture. B. Overlaet 2018. Mleiha, An Arab Kingdom on the Caravan Trails (Brussels 30.10-30.12.2018). Sharjah: Sharjah Archaeology Authority. Source: Objaverse 1.0 / Sketchfab
NeMig - A Bilingual News Collection and Knowledge Graph about Migration
<p>NeMig represents a bilingual news collection and knowledge graphs on the topic of migration. The news corpora in German and English were collected from online media outlets from Germany and the US, respectively. NeMIg contains rich textual and metadata information, sentiment and political orientation annotations, as well as named entities extracted from the articles' content and metadata and linked to Wikidata. The corresponding knowledge graphs (NeMigKG) built from each corpus are expanded with up to two-hop neighbors from Wikidata of the initial set of linked entities.</p> <p>NeMigKG comes in four flavors, for both the German, and the English corpora:</p> <ul> <li>Base NeMigKG: contains literals and entities from the corresponding annotated news corpus;</li> <li>Entities NeMigKG: derived from the Base NeMIg by removing all literal nodes, it contains only resource nodes;</li> <li>Enriched Entities NeMigKG: derived from the Entities NeMig by enriching it with up to two-hop neighbors from Wikidata, it contains only resource nodes and Wikidata triples;</li> <li>Complete NeMigKG: the combination of the Base and Enriched Entities NeMig, it contains both literals and resources.</li> </ul> <p>Information about uploaded files:</p> <p>(all files are b-zipped and in the N-Triples format.)</p> <p>A description of the <strong>NeMigKG files</strong> is provided in the table below:</p> <table align="left"> <caption>NeMigKG Files Description</caption> <thead> <tr> <th scope="col">File</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-metadata.nt.bz2</td> <td>Metadata about the dataset, described using void vocabulary.</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_types.nt.bz2</td> <td>Class definitions of news and event instances.</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_labels.nt.bz2</td> <td>Labels of instances.</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_related.nt.bz2</td> <td>Relations between news instances based on one another.</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_metadata_literals.nt.bz2</td> <td>Relations between news instances and metadata literals (e.g. URL, publishing date, modification date, sentiment label, political orientation of news outlets).</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_content_mapping.nt.bz2</td> <td>Mapping of news instances to content instances (e.g. title, abstract, body).</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_topic_mapping.nt.bz2</td> <td>Mapping of news instances to sub-topic instances.</td> </tr> <tr> <td> <p>nemig_<em>${language</em>}_ <em>$</em>{<em>graph_type</em>}-instances_sentiment_mapping.nt.bz2</p> </td> <td> <p>Mapping of news instances to sentiment classes.</p> </td> </tr> <tr> <td> <p>emig_<em>${language}</em>_ <em>${graph_type}</em>-instances_political_orientation_mapping.nt.bz2</p> </td> <td> <p>Mapping of news outlets instances to political orientation classes.</p> </td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_content_literals.nt.bz2</td> <td>Relations between content instances and corresponding literals (e.g. text of title, abstract, body).</td> </tr> <tr> <td> <p>nemig_<em>${language}_ ${graph_type}</em>-instances_sentiment_polorient_literals.nt.bz2</p> </td> <td> <p>Relations between instances and corresponding sentiment or political orientation literals.</p> </td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_metadata_resources.nt.bz2</td> <td>Relations between news or sub-topic instances and entities extracted from metadata (i.e. publishers, authors, keywords).</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-instances_event_mapping.nt.bz2</td> <td>Mapping of news instances to event instances.</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-event_resources.nt.bz2</td> <td>Relations between event instances and entities extracted from the text of the news (i.e. actors, places, mentions).</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-resources_provenance.nt.bz2</td> <td>Provenance information about the entities extracted from the text of the news (e.g. title, abstract, body).</td> </tr> <tr> <td>nemig_<em>$</em>{<em>language}</em>_ <em>$</em>{<em>graph_type}</em>-wiki_resources.nt.bz2</td> <td>Relations between Wikidata entities from news and their <em>k</em>-hop entity neighbors from Wikidata.</td> </tr> </tbody> </table> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p> </p> <p>The corresponding user data has been collected through online studies in Germany and the US. We used the participants' implicit feedback regarding their interest in an article to build their click history, and the explicit feedback in terms of news click behaviors to construct the impression logs. To protect user privacy, we assign each user an anonymized ID.</p> <p>The German and English user datasets are zip-compressed folders, which contain two files each.</p> <table> <caption>NeMig User Dataset File Description</caption> <tbody> <tr> <td><strong>File</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td> <p>behaviors.tsv</p> </td> <td> <p>The click history and impression logs of users.</p> </td> </tr> <tr> <td> <p>demographics_politics.tsv</p> </td> <td> <p>Demographic and political information of users.</p> </td> </tr> </tbody> </table> <p>The <strong>behaviors.tsv</strong> file contains the users' news click histories and the impression logs. It has 4 columns divided by the tab symbol:</p> <ul> <li> <p>Impression ID: the ID of an impression.</p> </li> <li> <p>User ID: The anonymized ID of an user.</p> </li> <li> <p>Click History: The news click history (list of news IDs) of a user before an impression.</p> </li> <li> <p>Impression Log: List of news displayed to the user in a session and the user's click behavior on them (1 for click, 0 for non-click).</p> </li> </ul> <p>The <strong>demographics_politics.tsv</strong> file contains detailed information about the users' demographics and political interests. It has columns divided by the tab symbol. An explanation of all the columns and the questions used in the online studies to collect this information is shown in the table below.</p> <table> <caption>Demographic and political user data description</caption> <thead> <tr> <th scope="col">Column Name</th> <th scope="col">Question in German study</th> <th scope="col">Scale in German</th> <th scope="col">Question in English study</th> <th scope="col">Scale in English</th> </tr> </thead> <tbody> <tr> <td><strong>Demographics</strong></td> <td> </td> <td> </td> <td> </td> <td> </td> </tr> <tr> <td>Gender</td> <td>Bitte geben Sie Ihr Geschlecht an</td> <td>0 = männlich<br> 1 = weiblich<br> 2 = divers<br> 3 = Keine Angabe</td> <td>Please indicate your gender.</td> <td>0 = male<br> 1 = female<br> 2 = other<br> 3 = no answer</td> </tr> <tr> <td>Age</td> <td>Bitte geben Sie Ihr Alter an </td> <td>1-120</td> <td>Please indicate your age.</td> <td>1-120</td> </tr> <tr> <td>Qualification</td> <td>Welches ist Ihr höchster Bildungsabschluss?</td> <td>0 = Kein Schulabschluss<br> 1 = Haupt-/Gesamtschulabschluss<br> 2 = Realschulabschluss, Mittlere Reife, Fachschulreife<br> 3 = Fachhochschulreife, Abitur<br> 4 = Studium mit Abschluss<br> 5 = Promotion<br> 6 = Keine Angabe</td> <td>Please indicate your highest educational qualification.</td> <td>0 = less than high school<br> 1 = high school/GED<br> 2 = Vo-tech/business school<br> 3 = some college<br> 4 = college degree<br> 5 = university degree<br> 6 = doctoral degree<br> 7 = no answer</td> </tr> <tr> <td>Nationality</td> <td>Welche Staatsangehörigkeit besitzen Sie?</td> <td>0 = Nur die deutsche Staatsangehörigkeit<br> 1 = Die deutsche und eine andere Staatsangehörigkeit<br> 2 = Nur eine andere Staatsangehörigkeit<br> 3 = Keine Angabe</td> <td>What is your citizenship?</td> <td>0 = U.S. citizenship<br> 1 = U.S. and another non-U.S. citizenship<br> 2 = Only non-U.S. citizenship<br> 3 = No Answer</td> </tr> <tr> <td>BornIn</td> <td>Sind Sie in Deutschland geboren?</td> <td>0 = Ja<br> 1 = Nein<br> 2 = Keine Angabe</td> <td>Were you born in the U.S.?</td> <td>0 = Yes<br> 1 = No<br> 2 = No answer</td> </tr> <tr> <td>ParentsBornIn</td> <td>Sind Ihre Eltern in Deutschland geboren?</td> <td>0 = Mein Vater und meine Mutter sind beide in Deutschland geboren<br> 1 = Mein Vater ist in Deutschland geboren, meine Mutter nicht<br> 2 = Meine Mutter ist in Deutschland geboren, mein Vater nicht<br> 3 = Weder meine Mutter noch mein Vater sind in Deutschland geboren<br> 4 = Keine Angabe</td> <td>Were your parents born in the U.S.?</td> <td>0 = My father and my mother were both born in the U.S.<br> 1 = My father was born in the U.S., my mother was not<br> 2 = My mother was born in the U.S., my father was not<br> 3 = Neither my mother nor my father were born in the U.S<br> 4 = No answer</td> </tr> <tr> <td>Income</td> <td>Was ist Ihr persönliches monatliches Nettoeinkommen (nach Abzug der Steuern)? Bitte geben Sie eine ungefähre Schätzung an, falls Sie die genaue Zahl nicht kennen.</td> <td>0 = Weniger als 1000 €<br> 1 = 1001 € bis 2000 €<br> 2 = 2001 € bis 3000 €<br> 3 = 3001 € bis 4000 €<br> 4 = 4001 € bis 5000 €<br> 5 = Mehr als 5000 €<br> 6 = Keine Angabe</td> <td>What is your personal monthly net income (after taxes)? Please give an approximate estimation in case you are unsure.</td> <td>0 = Less than 1000 $<br> 1 = 1001 $ to 2000 $<br> 2 = 2001 $ to 3000 $<br> 3 = 3001 $ to 4000 $<br> 4 = 4001 $ to 5000 $<br> 5 = More than 5000 $<br> 6 = No Answer</td> </tr> <tr> <td><strong>Empathy</strong></td> <td><strong>Wie sehr stimmen Sie den folgenden Aussagen zu?</strong></td> <td> <p><strong>7-point Likert scale</strong></p> <p><strong>1=Trifft überhaupt nicht zu<br> 7=Trifft voll und ganz zu</strong></p> </td> <td><strong>How strongly do you agree with the following statements?</strong></td> <td><strong>7-point Likert scale<br> <br> 1=Strongly disagree<br> 7=Strongly agree</strong></td> </tr> <tr> <td>EMP1</td> <td>Wenn jemand anderes erfreut ist, tendiere ich dazu auch erfreut zu sein.</td> <td> </td> <td>When someone else is feeling excited, I tend to get excited too.</td> <td> </td> </tr> <tr> <td>EMP2</td> <td>Es regt mich auf, wenn jemand respektlos behandelt wird.</td> <td> </td> <td>It upsets me to see someone being treated disrespectfully.</td> <td> </td> </tr> <tr> <td>EMP3</td> <td>Es macht mir Freude, andere aufzumuntern.</td> <td> </td> <td>I enjoy making other people feel better.</td> <td> </td> </tr> <tr> <td>EMP4</td> <td>Ich bin besorgt um Personen, die weniger Glück haben als ich.</td> <td> </td> <td>I have tender, concerned feelings for people less fortunate than me.</td> <td> </td> </tr> <tr> <td>EMP5</td> <td>Ich fühle, wenn andere traurig sind, selbst wenn sie nichts sagen.</td> <td> </td> <td>I can tell when others are sad even when they do not say anything.</td> <td> </td> </tr> <tr> <td>EMP6</td> <td>Meistens bin ich mit den Stimmungen anderer Leute im Einklang.</td> <td> </td> <td>I find that I am “in tune” with other people’s moods.</td> <td> </td> </tr> <tr> <td>EMP7</td> <td>Ich empfinde einen starken Drang zu helfen, wenn ich jemanden sehe, der aufgebracht ist.</td> <td> </td> <td>I get a strong urge to help when I see someone who is upset.</td> <td> </td> </tr> <tr> <td>EMP8</td> <td>Wenn ich jemanden sehe, der ausgenutzt wird, möchte ich die Person beschützen.</td> <td> </td> <td>When I see someone being taken advantage of, I feel kind of protective towards him\her.</td> <td> </td> </tr> <tr> <td><strong>Big5</strong></td> <td><strong>Ich bin...</strong></td> <td> <p><strong>7-point Likert scale</strong></p> <p><strong>0 = Sehr<br> 1 = Ziemlich<br> 2 = Etwas<br> 3 = Teils=Teils<br> 4 = Etwas<br> 5 = Zeimlich<br> 6 = Sehr</strong></p> </td> <td><strong>I see myself as...</strong></td> <td> <p><strong>7-point Likert scale</strong></p> <p><strong>1=Strongly disagree<br> 7=Strongly agree</strong></p> </td> </tr> <tr> <td>BIG1</td> <td>extrovertiert -- introvertiert</td> <td> </td> <td>...extroverted, enthusiastic</td> <td> </td> </tr> <tr> <td>BIG2</td> <td>emotional -- ausgeglichen</td> <td> </td> <td>...critical, quarrelsome</td> <td> </td> </tr> <tr> <td>BIG3</td> <td>aufgeschlossen -- festgelegt</td> <td> </td> <td>...dependable, self-disciplined</td> <td> </td> </tr> <tr> <td>BIG4</td> <td>barsch -- umgänglich</td> <td> </td> <td>...anxious, easily upset</td> <td> </td> </tr> <tr> <td>BIG5</td> <td>gewissenhaft -- nachlässig</td> <td> </td> <td>...open to new experiences, complex</td> <td> </td> </tr> <tr> <td>BIG6</td> <td>-</td> <td> </td> <td>...reserved, quiet</td> <td> </td> </tr> <tr> <td>BIG7</td> <td>-</td> <td> </td> <td>...sympathetic, warm</td> <td> </td> </tr> <tr> <td>BIG8</td> <td>-</td> <td> </td> <td>...disorganized, careless</td> <td> </td> </tr> <tr> <td>BIG9</td> <td>-</td> <td> </td> <td>..calm, emotionally stable</td> <td> </td> </tr> <tr> <td>BIG10</td> <td>-</td> <td> </td> <td>...conventional, uncreative</td> <td> </td> </tr> <tr> <td><strong>Ideological Polarization</strong></td> <td><strong>Im Folgenden sehen Sie eine Reihe von gegensätzlichen Aussagen.<br> Bitte geben Sie jeweils an, wie sehr Sie der Aussage zustimmen oder diese ablehnen.<br> Es gibt keine richtigen oder falschen Antworten.</strong></td> <td> <p><strong>7-point Likert scale</strong></p> <p><strong>0 = Sehr<br> 1 = Ziemlich<br> 2 = Etwas<br> 3 = Teils=Teils<br> 4 = Etwas<br> 5 = Zeimlich<br> 6 = Sehr</strong></p> </td> <td><strong>In the following, you will see a series of opposing statements.<br> Please indicate how strongly you agree or disagree with the statements.<br> There are no right or wrong answers.</strong></td> <td> <p><strong>7-point Likert scale</strong></p> <p><strong>1=Strongly disagree<br> 7=Strongly agree</strong></p> </td> </tr> <tr> <td>IPO1</td> <td>Deutschland sollte mehr Geflüchtete aufnehmen.</td> <td> </td> <td>The U.S. should take in more refugees.</td> <td> </td> </tr> <tr> <td>IPO2</td> <td>Deutschland hat schon zu viele Flüchtlinge aufgenommen.</td> <td> </td> <td>The U.S. should take in more refugees.</td> <td> </td> </tr> <tr> <td>IPO3</td> <td>Deutschland sollte sich für sichere und einfache Fluchtwege nach Europa einsetzen.</td> <td> </td> <td>The U.S. should advocate safe and easy escape routes to North America.</td> <td> </td> </tr> <tr> <td>IPO4</td> <td>Deutschland sollte sich dafür einsetzen, dass Flüchtlinge nicht einfach nach Europa kommen können.</td> <td> </td> <td>The U.S. should work to ensure that refugees cannot easily come to North America.</td> <td> </td> </tr> <tr> <td>IPO5</td> <td>Immigranten bemühen sich um ein friedliches Zusammenleben mit Deutschen.</td> <td> </td> <td>Immigrants strive for peaceful cohabitation with U.S.-Americans.</td> <td> </td> </tr> <tr> <td>IPO6</td> <td>Immigranten treten den Deutschen feindselig gegenüber.</td> <td> </td> <td>Immigrants are hostile toward U.S.-Americans.</td> <td> </td> </tr> <tr> <td>IPO7</td> <td>Immigranten wollen auf Kosten des deutschen Wohlstands leben.</td> <td> </td> <td>Immigrants want to live at the expense of U.S.-American prosperity.</td> <td> </td> </tr> <tr> <td>IPO8</td> <td>Immigranten helfen dabei, den deutschen Wohlstand zu sichern.</td> <td> </td> <td>Immigrants help in securing U.S.-American prosperity.</td> <td> </td> </tr> <tr> <td>IPO9</td> <td>Immigranten bedrohen die deutsche Kultur und Lebensweise.</td> <td> </td> <td>Immigrants threaten the U.S.-American culture and lifestyle.</td> <td> </td> </tr> <tr> <td>IPO10</td> <td>Immigranten bereichern die deutsche Kultur und Lebensweise.</td> <td> </td> <td>Immigrants enrich the U.S.-American culture and lifestyle.</td> <td> </td> </tr> <tr> <td>IPO11</td> <td>Immigranten sind krimineller und gewalttätiger als Deutsche.</td> <td> </td> <td>Immigrants are more criminal and more violent than U.S.-Americans.</td> <td> </td> </tr> <tr> <td>IPO12</td> <td>Immigranten sind nicht krimineller oder gewalttätiger als Deutsche.</td> <td> </td> <td>Immigrants are not more criminal and violent than U.S.-Americans.</td> <td> </td> </tr> <tr> <td><strong>Emotions</strong></td> <td><strong>Welche Emotionen empfinden Sie gegenüber Geflüchteten und Immigranten in Deutschland?</strong></td> <td><strong>7-point Likert Scale<br> <br> 1 = Stimme überhaupt nicht zu<br> 7 = Stimme voll zu</strong></td> <td><strong>Which emotions do you feel towards refugees and immigrants in the USA?</strong></td> <td><strong>7-point Likert Scale<br> <br> 1=Strongly disagree<br> 7=Strongly agree</strong></td> </tr> <tr> <td>EMO1</td> <td>Wut</td> <td> </td> <td>Anger</td> <td> </td> </tr> <tr> <td>EMO2</td> <td>Angst</td> <td> </td> <td>Fear</td> <td> </td> </tr> <tr> <td>EMO3</td> <td>Verachtung</td> <td> </td> <td>Contempt</td> <td> </td> </tr> <tr> <td>EMO4</td> <td>Trauer</td> <td> </td> <td>Grief</td> <td> </td> </tr> <tr> <td>EMO5</td> <td>Ekel</td> <td> </td> <td>Disgust</td> <td> </td> </tr> <tr> <td>EMO6</td> <td>Neid</td> <td> </td> <td>Envy</td> <td> </td> </tr> <tr> <td>EMO7</td> <td>Schadenfreude</td> <td> </td> <td>Gloat</td> <td> </td> </tr> <tr> <td>EMO8</td> <td>Mitleid</td> <td> </td> <td>Pity</td> <td> </td> </tr> <tr> <td>EMO9</td> <td>Mitgefühl</td> <td> </td> <td>Compassion</td> <td> </td> </tr> <tr> <td>EMO10</td> <td>Bewunderung</td> <td> </td> <td>Admiration</td> <td> </td> </tr> <tr> <td>EMO11</td> <td>Freude</td> <td> </td> <td>Joy</td> <td> </td> </tr> <tr> <td>EMO12</td> <td>Hoffnung</td> <td> </td> <td>Hope</td> <td> </td> </tr> <tr> <td>EMO13</td> <td>Dankbarkeit</td> <td> </td> <td>Gratitude</td> <td> </td> </tr> <tr> <td>EMO14</td> <td>Ehrfurcht</td> <td> </td> <td>Awe</td> <td> </td> </tr> <tr> <td><strong>Media Usage</strong></td> <td><strong>Informationen über die deutsche Politik bekomme ich aus/von:</strong></td> <td><strong>7-point Likert Scale<br> <br> 1=Nie<br> 7=Sehr häufig</strong></td> <td><strong>I receive information about US-American politics via:</strong></td> <td><strong>7-point Likert Scale<br> <br> 1=Never<br> 7=Very Often</strong></td> </tr> <tr> <td>MED1</td> <td>Zeitungen und Magazinen oder deren Internet-Angeboten (z.B. BILD-Zeitung/ bild.de, Der Spiegel/spiegel.de, ...) </td> <td> </td> <td>newspapers and magazines or their websites (e.g. New York Times, The Wallstreet Journal, ...)</td> <td> </td> </tr> <tr> <td>MED2</td> <td>dem Fernsehen oder deren Internet-Angeboten (z.B. ARD/ard.de, RTL /rtl.de, ...)</td> <td> </td> <td>TV networks or their websites (e.g. Fox News, CNN... )</td> <td> </td> </tr> <tr> <td>MED3</td> <td>dem Radio deren Internet-Angeboten (z.B. Energy/energy.de, Deutschlandfunk/deutschlandfunk.de, …) </td> <td> </td> <td>radio stations or their websites (e.g. WHTZ-FM, KIIS-FM, … )</td> <td> </td> </tr> <tr> <td>MED4</td> <td>Facebook (zur politischen Information)</td> <td> </td> <td>Facebook (for political information)</td> <td> </td> </tr> <tr> <td>MED5</td> <td>Twitter (zur politischen Information)</td> <td> </td> <td>Twitter (for political information)</td> <td> </td> </tr> <tr> <td>MED6</td> <td>Instagram (zur politischen Information)</td> <td> </td> <td>Instagram (for political information)</td> <td> </td> </tr> <tr> <td>MED7</td> <td>Messenger Diensten wie z.B. WhatsApp und Telegram (zur politischen Information)</td> <td> </td> <td>messenger services such as WhatsApp or Telegram (for political information)</td> <td> </td> </tr> <tr> <td>MED8</td> <td>YouTube (zur politischen Information)</td> <td> </td> <td>YouTube (for political information)</td> <td> </td> </tr> <tr> <td>MED9</td> <td>Politischen Blogs und/oder speziellen Nachrichtenanbietern, die es nur im Internet gibt</td> <td> </td> <td>political blogs and/or alternative news providers, which can only be found online</td> <td> </td> </tr> <tr> <td><strong>Participation</strong></td> <td><strong>Können Sie sich vorstellen, in naher Zukunft…</strong></td> <td><strong>7-point Likert Scale<br> <br> 1=Kann ich mir gar nicht vorstellen<br> <br> 7=Kann ich mir gar nicht vorstellen</strong></td> <td><strong>Please indicate how likely it is that you will engage in the following activities in the near future.</strong></td> <td><strong>7-point Likert Scale<br> <br> 1=Not likely at all<br> <br> 7=Very likely</strong></td> </tr> <tr> <td>PPA1</td> <td>… an einer politische Onlinediskussion zum Thema Immigration in Deutschland teilzunehmen?</td> <td> </td> <td>Participating in an online political discussion on the topic of immigration to the U.S.</td> <td> </td> </tr> <tr> <td>PPA2</td> <td>… eine politische Onlinepetition zum Thema Immigration in Deutschland zu unterschreiben?</td> <td> </td> <td>Signing an online political petition on the topic of immigration to the U.S.</td> <td> </td> </tr> <tr> <td>PPA3</td> <td>… eine/n Politiker/in in Deutschland zum Thema Immigration mit einer E-Mail oder über Social Media zu kontaktieren?</td> <td> </td> <td>Contacting a U.S.-American politician on the topic of immigration via e-mail or social media.</td> <td> </td> </tr> <tr> <td>PPA4</td> <td>… einer politischen Partei oder Gruppe auf Social Media zu folgen, die sich besonders im Themenfeld Immigration in Deutschland engagiert?</td> <td> </td> <td>Following a party or group on social media, that is particularly engaged in the field of immigration to the U.S.</td> <td> </td> </tr> <tr> <td>PPA5</td> <td>… einer politischen Partei oder Gruppe Geld zu spenden, die sich besonders im Themenfeld Immigration in Deutschland engagiert?</td> <td> </td> <td>Donating money to a political party or group that is especially involved in the field of immigration to the U.S.</td> <td> </td> </tr> <tr> <td>PPA6</td> <td>… an einer politischen Demonstration zum Thema Immigration in Deutschland teilzunehmen?</td> <td> </td> <td>Participating in a political demonstration on the topic of immigration to the U.S.</td> <td> </td> </tr> <tr> <td>PPA7</td> <td>… einer politischen Partei oder einer Gruppe beizutreten, die sich besonders im Themenfeld Immigration in Deutschland engagiert?</td> <td> </td> <td>Joining a political party or group that is especially involved in the field of immigration to the U.S.</td> <td> </td> </tr> <tr> <td>PPA8</td> <td>… für eine politische Partei, oder einer Gruppe Freiwilligenarbeit zu leisten, die sich besonders im Themenfeld Immigration in Deutschland engagiert?</td> <td> </td> <td>Volunteering for a political party or group that is especially involved in the field of immigration.</td> <td> </td> </tr> <tr> <td><strong>Perceived Polarization</strong></td> <td><strong>Wie bewerten Sie folgende Aussagen?</strong></td> <td><strong>7-point Likert Scale<br> <br> 1 = Stimme überhaupt nicht zu<br> 7 = Stimme voll zu</strong></td> <td><strong>How strongly do you agree or disagree with the following statements?</strong></td> <td> <p><strong>7-point Likert Scale</strong></p> <p><strong>1=Strongly disagree<br> 7=Strongly agree</strong></p> </td> </tr> <tr> <td>PRO1</td> <td>Die Anhänger der verschiedenen politischen Parteien in Deutschland stehen sich immer feindseliger gegenüber.</td> <td> </td> <td>Democratic and Republican partisans in the U.S. are increasingly hostile to one another. </td> <td> </td> </tr> <tr> <td>PRO2</td> <td>Die Anhänger der verschiedenen politischen Parteien in Deutschland haben sich immer weniger zu sagen.</td> <td> </td> <td>There is less and less common meeting ground between Democratic and Republican partisans in the U.S.</td> <td> </td> </tr> <tr> <td>PRO3</td> <td>Die Anhänger der verschiedenen politischen Parteien in Deutschland sind sehr polarisiert.</td> <td> </td> <td>Democratic and Republican partisans in the U.S. are very polarized.</td> <td> </td> </tr> <tr> <td>PRO4</td> <td>Die Meinungen zum Thema Immigration gehen in der deutschen Bevölkerung immer weiter auseinander.</td> <td> </td> <td>Opinions about immigration issues are increasingly diverging in U.S. society.</td> <td> </td> </tr> <tr> <td>PRO5</td> <td>Es wird immer schwieriger, in der deutschen Bevölkerung Einigung zu Fragen der Immigration zu erreichen.</td> <td> </td> <td>It is becoming increasingly difficult to reach agreement on immigration issues among the U.S. population.</td> <td> </td> </tr> <tr> <td>PRO6</td> <td>Das Thema Immigration spaltet die Menschen in Deutschland.</td> <td> </td> <td>Immigration issues are dividing the people in the U.S.</td> <td> </td> </tr> <tr> <td><strong>Affective polarization</strong></td> <td><strong>Hier sehen Sie die Liste aller im Bundestag vertretenen Parteien.<br> Bitte markieren Sie auf jeder der Skalen wie positiv oder negativ Sie für die jeweilige Partei empfinden.</strong></td> <td><strong>0 (negative) to 100 (positive)</strong></td> <td><strong>In the following we would like to know about your party identification.<br> Please mark on the scale how warm or cold you feel towards the respective parties.</strong></td> <td><strong>0 (negative) to 100 (positive)</strong></td> </tr> <tr> <td>CDU / Rep</td> <td>CDU</td> <td> </td> <td>Republican </td> <td> </td> </tr> <tr> <td>SPD / Dem</td> <td>SPD</td> <td> </td> <td>Democrat</td> <td> </td> </tr> <tr> <td>GRU</td> <td>GRU</td> <td> </td> <td>-</td> <td> </td> </tr> <tr> <td>FDP</td> <td>FDP</td> <td> </td> <td>-</td> <td> </td> </tr> <tr> <td>LIN</td> <td>LIN</td> <td> </td> <td>-</td> <td> </td> </tr> <tr> <td>AFD</td> <td>AFD</td> <td> </td> <td>-</td> <td> </td> </tr> <tr> <td><strong>Political Scale</strong> (POL1)</td> <td><strong>Wo würden Sie Ihren eigenen politischen Standpunkt auf der folgenden Skala einordnen?</strong></td> <td><strong>11-point Likert Scale<br> <br> 1 = Links<br> 6 = Mitte<br> 11 = Rechts</strong></td> <td><strong>Where on the scale would you place your political point of view?</strong></td> <td><strong>11-point Likert Scale<br> <br> 1 = Left<br> 6 = Center<br> 11 = Right</strong></td> </tr> <tr> <td><strong>Political Topics</strong></td> <td><strong>Bitte geben Sie an, inwiefern die folgenden Aussagen auf Sie zutreffen?</strong></td> <td><strong>7-point Likert Scale<br> <br> 1 = Trifft überhaupt nicht zu<br> 7 = Trifft voll und ganz zu</strong></td> <td><strong>Please indicate how strongly you agree or disagree with the following statements.</strong></td> <td><strong>7-point Likert Scale<br> <br> 1 = Strongly disagree<br> 7 = Strongly agree</strong></td> </tr> <tr> <td>POL2</td> <td>Ich interessiere mich im Allgemeinen sehr für Politik.</td> <td> </td> <td>I am generally very interested in politics.</td> <td> </td> </tr> <tr> <td>POL3</td> <td>Ich informiere mich regelmäßig über das aktuelle politische Geschehen in Deutschland.</td> <td> </td> <td>I regularly inform myself about current political affairs in the U.S..</td> <td> </td> </tr> <tr> <td>POL4</td> <td>Mir ist es wichtig, über das aktuelle politische Geschehen in Deutschland informiert zu sein.</td> <td> </td> <td>It is important to me to be informed about current political affairs in the U.S..</td> <td> </td> </tr> <tr> <td>POL5</td> <td>Ich lese viele politische Nachrichtenartikel.</td> <td> </td> <td>I read many political news articles.</td> <td> </td> </tr> <tr> <td>POL6</td> <td>Im Vergleich zu meinen Freunden bin ich ein Experte für das aktuelle politische Geschehen.</td> <td> </td> <td>Compared to my friends, I am an expert on current political affairs.</td> <td> </td> </tr> <tr> <td>POL7</td> <td>Ich interessiere mich sehr für das Thema Immigration und die Immigrationspolitik in Deutschland.</td> <td> </td> <td>I am very interested in the topic of immigration and U.S. immigration policy.</td> <td> </td> </tr> <tr> <td>POL8</td> <td>Ich informiere mich regelmäßig über Neuigkeiten zum Thema Immigration und Immigrationspolitik in Deutschland.</td> <td> </td> <td>I try to keep up-to-date with news about immigration and U.S. immigration policy.</td> <td> </td> </tr> <tr> <td>POL9</td> <td>Mir ist es wichtig, über die aktuellen Entwicklungen zum Thema Immigration und Immigrationspolitik in Deutschland informiert zu sein.</td> <td> </td> <td>It is important to me to be informed about current developments in the field of immigration and U.S. immigration policy.</td> <td> </td> </tr> <tr> <td><strong>Prosocial behavior</strong></td> <td><strong>Bitte geben Sie nachfolgend an wie sehr Sie den Aussagen zustimmen.</strong></td> <td> </td> <td><strong>Please indicate how strongly you agree or disagree with the following statements. </strong> </td> <td> </td> </tr> <tr> <td>PRO1</td> <td>Ich wäre bereit, Gegenstände (z. B. Kleidung, Spielzeug, Möbel, Elektrogeräte) für Geflüchtete in Deutschland zu spenden.</td> <td>7-point Likert Scale<br> <br> 1 = Stimme überhaupt nicht zu<br> 7 = Stimme voll zu</td> <td>I would be willing to donate items (e.g. clothing, toys, furniture, electronics) to refugees living in the U.S.</td> <td>7-point Likert Scale<br> <br> 1 = Strongly disagree<br> 7 = Strongly agree</td> </tr> <tr> <td>PRO2</td> <td>Ich wäre dazu bereit, Geflüchtete im Alltag zu unterstützen (z. B. Behördengänge begleiten, Deutschunterricht geben, eine gemeinsame Freizeitaktivität unternehmen).</td> <td>7-point Likert Scale<br> <br> 1 = Stimme überhaupt nicht zu<br> 7 = Stimme voll zu</td> <td>I would be willing to support refugees living in the U.S. with their everyday life (e.g. support with bureaucratic procedures, teaching English, leisure activities).</td> <td>7-point Likert Scale<br> <br> 1 = Strongly disagree<br> 7 = Strongly agree</td> </tr> <tr> <td>PRO3</td> <td>Ich wäre bereit __ € für Geflüchtete in Deutschland zu spenden.</td> <td>float number >= 0</td> <td>I am willing to make a one-time donation of __$ for refugees in the U.S.</td> <td>float number >= 0</td> </tr> <tr> <td>PRO4</td> <td>Wie häufig haben Sie beruflich (z. B. auf der Arbeit, im Studium) Kontakt mit Menschen mit Migrationshintergrund?</td> <td> <p>7-point Likert Scale</p> <p>1 = Nie<br> 7 = Sehr häufig</p> </td> <td>How often do you have professional contact (e.g. at work or at school) with immigrants?</td> <td> <p>7-point Likert Scale</p> <p>1 = Never<br> 7 = Very often</p> </td> </tr> <tr> <td>PRO5</td> <td>Wie häufig haben Sie privat (z. B. Freunde, Verwandte, Bekannte) Kontakt mit Menschen mit Migrationshintergrund?</td> <td> <p>7-point Likert Scale</p> <p>1 = Nie<br> 7 = Sehr häufig</p> </td> <td>How often do you have private contact (e.g. friends, relatives, acquaintances) with immigrants?</td> <td> <p>7-point Likert Scale</p> <p>1 = Never<br> 7 = Very often</p> </td> </tr> </tbody> </table> <p> </p>
PaCL: A Multi-Domain and Bilingual Benchmark for Cross-Lingual Patent Ranking
Open the record for dataset details and reuse information.
Uyghur-Chinese adult bilinguals' construal of caused motion events
<p>This is data for an article on Uyghur-Chinese adult bilinguals' construal of caused motion events. </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.